TY - JOUR
T1 - EMSx
T2 - a numerical benchmark for energy management systems
AU - Le Franc, Adrien
AU - Carpentier, Pierre
AU - Chancelier, Jean Philippe
AU - De Lara, Michel
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.
PY - 2023/8/1
Y1 - 2023/8/1
N2 - Inserting renewable energy in the electric grid in a decentralized manner is a key challenge of the energy transition. However, at local scale, both production and demand display erratic behavior, which makes it challenging to match them. It is the goal of Energy Management Systems (EMS) to achieve such balance at least cost. We present EMSx, a numerical benchmark for testing control algorithms for the management of electric microgrids equipped with a photovoltaic unit and an energy storage system. EMSx is made of three key components: the EMSx dataset, provided by Schneider Electric, contains a diverse pool of realistic microgrids with a rich collection of historical observations and forecasts; the EMSx mathematical framework is an explicit description of the assessment of electric microgrid control techniques and algorithms; the EMSx software EMSx.jl is a package, implemented in the Julia language, which enables to easily implement a microgrid controller and to test it. All components of the benchmark are publicly available, so that other researchers willing to test controllers on EMSx may reproduce experiments easily. Eventually, we showcase the results of standard microgrid control methods, including Model Predictive Control, Open Loop Feedback Control and Stochastic Dynamic Programming.
AB - Inserting renewable energy in the electric grid in a decentralized manner is a key challenge of the energy transition. However, at local scale, both production and demand display erratic behavior, which makes it challenging to match them. It is the goal of Energy Management Systems (EMS) to achieve such balance at least cost. We present EMSx, a numerical benchmark for testing control algorithms for the management of electric microgrids equipped with a photovoltaic unit and an energy storage system. EMSx is made of three key components: the EMSx dataset, provided by Schneider Electric, contains a diverse pool of realistic microgrids with a rich collection of historical observations and forecasts; the EMSx mathematical framework is an explicit description of the assessment of electric microgrid control techniques and algorithms; the EMSx software EMSx.jl is a package, implemented in the Julia language, which enables to easily implement a microgrid controller and to test it. All components of the benchmark are publicly available, so that other researchers willing to test controllers on EMSx may reproduce experiments easily. Eventually, we showcase the results of standard microgrid control methods, including Model Predictive Control, Open Loop Feedback Control and Stochastic Dynamic Programming.
KW - Electric microgrid
KW - Multistage stochastic optimization
KW - Numerical benchmark
UR - https://www.scopus.com/pages/publications/85101067475
U2 - 10.1007/s12667-020-00417-5
DO - 10.1007/s12667-020-00417-5
M3 - Article
AN - SCOPUS:85101067475
SN - 1868-3967
VL - 14
SP - 817
EP - 843
JO - Energy Systems
JF - Energy Systems
IS - 3
ER -